Communications of the ACM
Researchers Apply Hypergraphs to Covid-19 Complexity
For researchers at Pacific Northwest National Laboratory, understanding viral infection is a matter of mathematics rather than a purely molecular analysis. They are using an advanced mathematical tool called hypergraphs to identify how human cells respond to viral infection, including the new coronavirus. The key proteins participating in that response might be targets for developing medicines to treat Covid-19.
PNNL mathematician Emilie Purvine and computational biologist Jason McDermott recently presented their work virtually at the The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, an annual conference for data mining, data science, and analytics.
In a key step, the team tested the new approach with data from a similar virus, the coronavirus that causes Severe Acute Respiratory Syndrome (SARS).
The PNNL team found that the results from the new method matched up with data previously collected about that virus. Using hypergraphs, the team identified and ranked the activity of several genes now known to be important to the activity of the virus that caused the SARS-1 outbreak.
"Our work independently identified the same genes known to be important with SARS activity. This was an important step to take before applying our work to the virus that causes Covid-19," McDermott says.
The PNNL team is applying the new technology to the current virus, using hypergraphs to sort out and rank the importance of many of the hundreds of genes active in Covid-19.
From Pacific Northwest National Laboratory
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